Room Pricing: Using Relevant Data and Machine Learning for Precise Pricing
By Gino Engels Co-Founder, OTA Insight | November 04, 2018
Emerging technology is always a hot topic. It's gone from Big Data to data science, artificial intelligence, machine learning, predictive analytics, and most recently, blockchain. Keeping up with these technologies is never easy, especially for the hotelier focused on running a strong, profitable operation with a memorable guest experience.
As a third-party partner to the industry, we pride ourselves on being shepherds across this emerging technology landscape. There are new channels emerging regularly, such as alternative accommodations and niche booking engines; hoteliers are bombarded with new places to distribute their content.
And with each new channel comes an additional burden: ensuring parity and competitiveness of room pricing across channels.
For us at OTA Insight, we believe that Big Data is an overused-but-descriptive term that has helped us all understand the latent value within large datasets. The evolution of machine learning, which empowers decision-making to happen in real-time without further human input, now means that this value can be rapidly unlocked in real-time.
This evolution to real-time has created a world in which room rates are adjusted in seconds, rather than days. Dynamic pricing allows hotels to change prices rapidly in response to changing market demand.
While this maximizes profitability, it also dramatically increases complexity. It's not unheard of for there to be multiple price changes in a given hour. Consider the variables at play: seasonality, local events and conferences, room types, amenities, variations of packages (such as breakfast included)...the rate permutations across hotels in a given market can easily run into the millions.
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